22 research outputs found

    Collaboration In Software Engineering Projects: A Theory Of Coordination

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    Coordination of engineering decisions is a central concern of software engineering. We present a theory in which coordination of engineering decisions is modeled as a distributed constraint satisfaction problem (DCSP). We derive six hypotheses, predicting how the distribution of decisions over developers and the density of constraints among decisions will affect development time, probability that a file contains a field defect, and developer productivity. We test these hypotheses using data from a commercial project. We find support for all hypotheses predicting detrimental effects from poor distribution of decisions over developers. The effects of constraint density were mixed, showing that dense constraints slowed development but did not significantly affect productivity. Dense data dependencies increased the chances that a file contained a field defect, but, very surprisingly, dense call dependencies significantly lowered the chances that a file contained a field defect. We discuss the implications of these findings

    The impact of the conflict on solving distributed constraint satisfaction problems

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    Distributed Constraint Satisfaction Problems (DCSPs) involve a vast number of AI andMulti-Agent problems. Many important efforts have been recen accomplished for solving these kinds of problems using both backtracking-based and mediation-based methods. One of the most successful mediation based algorithms in this field is Asynchronous Partial Overlay (APO) algorithm. By choosing some agents as mediators, APO tries to centralize portions of the distributed problem, and then each mediator tries to solve its centralized sub-problem. This work continues until the whole problem is solved. This paper presents a new strategy to select mediators. The main idea behind this strategy is that the number of mediators conflicts (violated constraints) impacts directly on its performance. Experimental results show that choosing the mediators with the most number of conflicts not only leads to considerable decrease in APO complexity, but also it can decrease the complexity of the other extensions of the APO such as IAPO algorithm. MaxCAPO and MaxCIAPO are two new expansions of APO which introduce this idea and are presented in this article. The results of using this mediator selection strategy show a rapid and desirable improvement over various parameters in comparison with APO and IAP

    Dynamic constraint satisfaction approach to hospital scheduling optimization

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    L' elaborato tratta il problema dell'Hospital Scheduling Optimization : l'ottimizzazione della gestione delle risorse di un ospedale attraverso una schedulazione efficiente dei singoli pazienti ospiti della struttura, mirando a massimizzare il throughput dei pazienti assistiti mantenendo, nello stesso tempo, il Minimum Service Level garantito. Dopo una trattazione sullo stato dell'arte degli approcci risolutivi a questo problema l'elaborato descrive il metodo di risoluzione mediante l'uso dei Dynamic Constraint Satisfaction Problems proponendo prima di tutto una modellazione dettagliata della realtĂ  ospedaliera e, successivamente, un'implementazione in Java. Sono inoltre descritti i risultati ottenuti dai vari tipi di simulazione, che ricalcano gli scenari tipici dell'ambiente ospedaliero, mirate a misurare le performance di quest'implementazion

    Distributed Target Engagement in Large-scale Mobile Sensor Networks

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    Sensor networks comprise an emerging field of study that is expected to touch many aspects of our life. Research in this area was originally motivated by military applications. Afterward sensor networks have demonstrated tremendous promise in many other applications such as infrastructure security, environment and habitat monitoring, industrial sensing, traffic control, and surveillance applications. One key challenge in large-scale sensor networks is the efficient use of the network's resources to collect information about objects in a given Volume of Interest (VOI). Multi-sensor Multi-target tracking in surveillance applications is an example where the success of the network to track targets in a given volume of interest, efficiently and effectively, hinges significantly on the network's ability to allocate the right set of sensors to the right set of targets so as to achieve optimal performance. This task can be even more complicated if the surveillance application is such that the sensors and targets are expected to be mobile. To ensure timely tracking of targets in a given volume of interest, the surveillance sensor network needs to maintain engagement with all targets in this volume. Thus the network must be able to perform the following real-time tasks: 1) sensor-to-target allocation; 2) target tracking; 3) sensor mobility control and coordination. In this research I propose a combination of the Semi-Flocking algorithm, as a multi-target motion control and coordination approach, and a hierarchical Distributed Constraint Optimization Problem (DCOP) modelling algorithm, as an allocation approach, to tackle target engagement problem in large-scale mobile multi-target multi-sensor surveillance systems. Sensor-to-target allocation is an NP-hard problem. Thus, for sensor networks to succeed in such application, an efficient approach that can tackle this NP-hard problem in real-time is disparately needed. This research work proposes a novel approach to tackle this issue by modelling the problem as a Hierarchical DCOP. Although DCOPs has been proven to be both general and efficient they tend to be computationally expensive, and often intractable for large-scale problems. To address this challenge, this research proposes to divide the sensor-to-target allocation problem into smaller sub-DCOPs with shared constraints, eliminating significant computational and communication costs. Furthermore, a non-binary variable modelling is presented to reduce the number of inter-agent constraints. Target tracking and sensor mobility control and coordination are the other main challenges in these networks. Biologically inspired approaches have recently gained significant attention as a tool to address this issue. These approaches are exemplified by the two well-known algorithms, namely, the Flocking algorithm and the Anti-Flocking algorithm. Generally speaking, although these two biologically inspired algorithms have demonstrated promising performance, they expose deficiencies when it comes to their ability to maintain simultaneous reliable dynamic area coverage and target coverage. To address this challenge, Semi-Flocking, a biologically inspired algorithm that benefits from key characteristics of both the Flocking and Anti-Flocking algorithms, is proposed. The Semi-Flocking algorithm approaches the problem by assigning a small flock of sensors to each target, while at the same time leaving some sensors free to explore the environment. Also, this thesis presents an extension of the Semi-Flocking in which it is combined with a constrained clustering approach to provide better coverage over maneuverable targets. To have a reliable target tracking, another extension of Semi-Flocking algorithm is presented which is a coupled distributed estimation and motion control algorithm. In this extension the Semi-Flocking algorithm is employed for the purpose of a multi-target motion control, and Kalman-Consensus Filter (KCF) for the purpose of motion estimation. Finally, this research will show that the proposed Hierarchical DCOP algorithm can be elegantly combined with the Semi-Flocking algorithm and its extensions to create a coupled control and allocation approach. Several experimental analysis conducted in this research illustrate how the operation of the proposed algorithms outperforms other approaches in terms of incurred computational and communication costs, area coverage, target coverage for both linear and maneuverable targets, target detection time, number of undetected targets and target coverage in noise conditions sensor network. Also it is illustrated that this algorithmic combination can successfully engage multiple sensors to multiple mobile targets such that the number of uncovered targets is minimized and the sensors' mean utilization factor sensor surveillance systems.is maximized

    Large-Scale Distributed Coalition Formation

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    The CyberCraft project is an effort to construct a large scale Distributed Multi-Agent System (DMAS) to provide autonomous Cyberspace defense and mission assurance for the DoD. It employs a small but flexible agent structure that is dynamically reconfigurable to accommodate new tasks and policies. This document describes research into developing protocols and algorithms to ensure continued mission execution in a system of one million or more agents, focusing on protocols for coalition formation and Command and Control. It begins by building large-scale routing algorithms for a Hierarchical Peer to Peer structured overlay network, called Resource-Clustered Chord (RC-Chord). RC-Chord introduces the ability to efficiently locate agents by resources that agents possess. Combined with a task model defined for CyberCraft, this technology feeds into an algorithm that constructs task coalitions in a large-scale DMAS. Experiments reveal the flexibility and effectiveness of these concepts for achieving maximum work throughput in a simulated CyberCraft environment

    Regulatory Monitors: Policing Firms in the Compliance Era

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    Like police officers patrolling the streets for crime, the front line for most large business regulators — Environmental Protection Agency (EPA) engineers, Consumer Financial Protection Bureau (CFPB) examiners, and Nuclear Regulatory Commission (NRC) inspectors, among others — decide when and how to enforce the law. These regulatory monitors guard against toxic air, financial ruin, and deadly explosions. Yet whereas scholars devote considerable attention to police officers in criminal law enforcement, they have paid limited attention to the structural role of regulatory monitors in civil law enforcement. This Article is the first to chronicle the statutory rise of regulatory monitors and to situate them empirically at the core of modern administrative power. Since the Civil War, often in response to crises, the largest federal regulators have steadily accrued authority to collect documents remotely and enter private space without any suspicion of wrongdoing. Those exercising this monitoring authority within agencies administer the law at least as much as the groups that are the focus of legal scholarship: enforcement lawyers, administrative law judges, and rule writers. Regulatory monitors wield sanctions, influence rulemaking, and create quasi-common law. Moreover, they offer a better fit than lawyers for the modern era of “collaborative governance” and corporate compliance departments, because their principal function — information collection — is less adversarial. Yet unlike lawsuits and rulemaking, monitoring-based decisions are largely unobservable by the public, often unreviewable by courts, and explicitly excluded by the Administrative Procedure Act (APA). The regulatory monitor function can thus be more easily ramped up or deconstructed by the President, interest groups, and agency directors. A better understanding of regulatory monitors — and their relationship with regulatory lawyers — is vital to designing democratic accountability not only during times of political transition, but as long as they remain a central pillar of the administrative state

    Earth Observatory Satellite system definition study. Report 5: System design and specifications. Volume 1: Baseline system description

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    A system baseline design oriented to the requirements of the next generation of Earth Observatory Satellite missions is presented. The first mission (EOS-A) is envisioned as a two-fold mission which (1) provides a continuum of data of the type being supplied by ERTS for the emerging operational applications and also (2) expands the research and development activities for future instrumentation and analysis techniques. The baseline system specifically satisfies the requirements of this first mission. However, EOS-A is expected to be the first of a series of earth observation missions. Thus the baseline design has been developed so as to accommodate these latter missions effectively as the transition is made from conventional, expendable launch vehicles and spacecraft to the Shuttle Space Transportation System era. Further, a subset of alternative missions requirements including Seasat, SEOS, SMM and MSS-5 have been analyzed to verify that the spacecraft design to serve a multi-mission role is economically sound. A key feature of the baseline system design is the concept of a modular observatory system whose elements are compatible with varying levels of launch vehicle capability. The design configuration can be used with either the Delta or Titan launch vehicles and will adapt readily to the space shuttle when that system becomes available in the early 1980's
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